Gray Matter Density of Mathematicians

Below is the abstact from the article “Increased Gray Matter Density in the Parietal Cortex of Mathematicians: A Voxel-Based Morphometry Study” by K. Aydin, A. Ucar, K.K. Oguz, O.O. Okur, A. Agayev, Z. Unal, S. Yilmaz, and C. Ozturk published in the American Journal of NeuroRadiology (AJNR), Nov-Dec 2007:

 

 

BACKGROUND AND PURPOSE:

The training to acquire or practicing to perform a skill, which may lead to structural changes in the brain, is called experience-dependent structural plasticity. The main purpose of this cross-sectional study was to investigate the presence of experience-dependent structural plasticity in mathematicians’ brains, which may develop after long-term practice of mathematic thinking.

 

MATERIALS AND METHODS:

Twenty-six volunteer mathematicians, who have been working as academicians, were enrolled in the study. We applied an optimized method of voxel-based morphometry in the mathematicians and the age- and sex-matched control subjects. We assessed the gray and white matter density differences in mathematicians and the control subjects. Moreover, the correlation between the cortical density and the time spent as an academician was investigated.

 

RESULTS:

 

We found that cortical gray matter density in the left inferior frontal and bilateral inferior parietal lobules of the mathematicians were significantly increased compared with the control subjects. Furthermore, increase in gray matter density in the right inferior parietal lobule of the mathematicians was strongly correlated with the time spent as an academician (r = 0.84; P < .01). Left-inferior frontal and bilateral parietal regions are involved in arithmetic processing. Inferior parietal regions are also involved in high-level mathematic thinking, which requires visuospatial imagery, such as mental creation and manipulation of 3D objects.

 

CONCLUSION:

 

The voxel-based morphometric analysis of mathematicians’ brains revealed increased gray matter density in the cortical regions related to mathematic thinking. The correlation between cortical density increase and the time spent as an academician suggests experience-dependent

structural plasticity in mathematicians’ brains.

Introduction to fMRI Analysis

A very good set of slides introducing fMRI analysis methods, and
statistical inference - from Prof. Vince Calhoun's course at:

http://www.ece.unm.edu/~vcalhoun/courses/fMRI_Spring07/fmricourse.htm

Also, with more emphasis on the physics and neuroscientific aspects -
H.583 at MIT:

http://ocw.mit.edu/OcwWeb/Health-Sciences-and-Technology/HST-583Fall-2004/CourseHome/index.htm

Re: Mathematics in Brain Imaging

This is good... I think the workshop at MBI in June also has some real good ones on similar topics...

raghu

On Fri, Aug 1, 2008 at 3:59 PM, firdaus.janoos <firdaus.janoos@gmail.com> wrote:

The presentations (audio + video + slides) for the summer school on Mathematics in Brain Imaging hosted by ULCA's Institute for Pure and Applied Mathematics: https://www.ipam.ucla.edu/schedule.aspx?pc=mbi2008

They will be adding more slides as the speakers send them.

There were some very good lectures/talks - esp. in the computational anatomy week (14-19 July). I've been told that the talks by Michael Miller, Sarang Joshi, Xavier Pennec and Baba Vemuri were particularly good.

Also, in the functional imaging week (21-25 July), some excellent talks, esp. on ICA, validation, MCP correction and machine learning methods.

--
Raghu Machiraju, Associate Professor,
The Ohio State University, Columbus, OH 43210

Mathematics in Brain Imaging

The presentations (audio + video + slides) for the summer school on Mathematics in Brain Imaging hosted by ULCA's Institute for Pure and Applied Mathematics: https://www.ipam.ucla.edu/schedule.aspx?pc=mbi2008

They will be adding more slides as the speakers send them.

There were some very good lectures/talks - esp. in the computational anatomy week (14-19 July). I've been told that the talks by Michael Miller, Sarang Joshi, Xavier Pennec and Baba Vemuri were particularly good.

Also, in the functional imaging week (21-25 July), some excellent talks, esp. on ICA, validation, MCP correction and machine learning methods.